MAI is looking to solve the problem of democratizing advanced advertising technology by making cutting-edge marketing tools accessible to small and mid-sized businesses, and is seeking a Software Engineer Intern to contribute to the development of their AI-native product.
Requirements
- Currently pursuing a PhD in Computer Science or a related quantitative field with a focus on areas such as machine learning, artificial intelligence, large language models, or distributed systems.
- A strong theoretical foundation and a proven ability to conduct and apply original research.
- Proficiency in a modern programming language (e.g., Python).
- Passion for turning groundbreaking research into robust, scalable production systems.
- Machine Learning/AI: Experience implementing or fine-tuning models from research papers, or a strong publication record in top-tier conferences.
- Large Language Models (LLMs): Hands-on experience with LLM-based systems, including a deep understanding of their underlying architectures and challenges like hallucination or prompt engineering.
- Complex Systems: Experience designing and debugging large-scale distributed systems or data pipelines.
Responsibilities
- Architect and Prototype Novel Solutions: You will apply your advanced research skills to design and prototype new features for our core agentic platform, exploring cutting-edge algorithms and architectures to improve our autonomous agents' capabilities.
- Contribute to a Robust Platform: Design, build, and maintain the critical infrastructure that supports our autonomous agents, focusing on scalability, reliability, and performance.
- Tackle Complex Challenges: Solve novel, ambiguous problems at the intersection of AI, large-scale systems, and high-stakes performance marketing.
- Collaborate and Grow: Work closely with a world-class team of engineers and researchers, engaging in design discussions, code reviews, and knowledge sharing to advance our collective understanding of agentic systems.
- Exploring new agentic architectures and running experiments to evaluate their performance.
- Applying and adapting the latest research papers on topics like memory, reasoning, or long-term planning into our production systems.
- Conducting rigorous performance analysis on our ML pipelines to identify and resolve bottlenecks at a fundamental level.
Other
- Currently pursuing a PhD in Computer Science or a related quantitative field.
- Passion for turning groundbreaking research into robust, scalable production systems.
- Ability to work closely with a world-class team of engineers and researchers.
- Autonomy over your work with mentorship support from an assigned team member.
- A drive to learn and grow, with a holistic approach to hiring.
